1. Field of the Invention
The present invention is related to the field of arrays more specifically to array systems.
2. Description of the Related Art
DNA arrays are commonly used to make quantitative or relative measurements of gene expression. They provide a medium for matching known and unknown DNA samples based on base-pairing rules and automating the process of identifying the unknowns. In general, arrays are described as macroarrays or microarrays, the difference being the size of the sample spots. Macroarrays contain sample spot sizes of about 300 microns or larger and can be easily imaged by existing gel and blot scanners. The sample spot sizes in microarrays are typically less than 200 microns in diameter and these arrays usually contain thousands of spots.
The microarrays contain nucleotide sequences corresponding to known genes or expressed sequence tags. A single microarray can contain thousands of genes, which may represent a significant subset of the genes, or even the entire genome, of an organism. A comparison of cells or tissues from experimental and control preparations provides data on differences in expression levels between the two conditions. For this purpose, mRNA is extracted from a sample, converted to complementary DNA (cDNA) and tagged with a fluorescent label. In a typical microarray experiment, cDNA from one sample (sample A) is labeled with a first dye that fluoresces in the red and cDNA from another sample (sample B) is labeled with a different dye that fluoresces in the green. The fluorescent red and green cDNA samples are then applied to a microarray that contains DNA fragments (oligonucleotides) corresponding to thousands of genes. If a DNA sequence probe is present on the microarray and its target complement is present in one or both samples, the sequences bind, and a fluorescent signal can be detected at the specific spot on the array. The signals are generally picked up using a “scanner” which creates a digital image of the array. The red to green fluorescence ratio in each spot reflects the relative expression of a given gene in the samples A and B.
Current microarray analyses rely on normalization and quality control methods that often assume evenly distributed changes, and/or absence of global shifts in gene expression across the array surface. Spotted microarray features such as housekeeping genes, sample pools, genomic DNA, or all genes on a microarray are typically used for normalization. Normalization based on these features is not always appropriate, especially for smaller focussed arrays (versus whole genome microarrays) where unbalanced changes are likely to occur, and will have significant effects on the relative hybridization signal intensities between biological samples. As a result, normalization based on such features will give rise to inaccurate interpretations of gene expression data.
According to WO2004/064482, normalization and quality assessment of microarray data, where unbalanced gene expression is anticipated, can be accomplished by the addition of several different external, non-species nucleic acid targets of different concentrations into the RNA sample of interest prior to labelling and hybridization. Different concentrations of external control targets are chosen to mimic a broad range of expression profiles. Probes complimentary to the external targets are printed at equivalent concentrations on the microarray. Variation between external control target concentrations in the sample results in different fluorescence intensities detected for each external control probe. Since detection of the different external controls will be equivalent between RNA samples, and are not affected by unbalanced or global shifts in gene expression within the RNA sample of interest, they can be used for accurate normalization and interpretation of gene expression data from focussed microarrays.
The drawback to using an external control, where varying amounts of different targets are added to the RNA sample of interest, is that it requires accurate measurement of extremely small quantities of those several RNA targets at low concentrations. The technical error associated with measurements at the low range required for microarray analysis results in unacceptable variation between samples that will have a significant influence on normalization and interpretation of gene expression data. In addition, the optimization and preparation of multiple external control targets and probes is time-consuming and costly.
Accordingly, there is a need for a microarray system that allows for more accuracy in the normalization of the data.